Angewandte Datenverarbeitung und Visualisierung (WiSe23/24)
  • D. Palleschi
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  1. Overview
  2. Syllabus
  • Overview
    • Course Overview
    • Syllabus
    • Kursübersicht
  • Course mats
    • 1  Einführung in R und RStudio
  • Reports
    • Bericht 1
    • Bericht 2
    • Bericht 3
  • References

Syllabus

Woche Datum Thema Vorbereitung
1 2023-10-18

Intro to R

[📚 R4DS - Ch 1 (Introduction)
📚 R4DS - Ch 3 (Workflow: Basics)](https://r4ds.hadley.nz/intro
https://r4ds.hadley.nz/workflow-basics)

2 2023-10-25

Data Viz 1: Distributions and comparing groups

R4DS - Ch. 1 (Introduction)
📚 R4DS - Ch. 3 (Workflow: Basics)

3 2023-11-01

Wrangling 1: Transforming data

📚 R4DS - Chp 6

4 2023-11-08

Dynamic reports with Quarto

📚 ggplot2-book - Chp 5

5 2023-11-15

Regular Expressions

📚 R4DS - Chp 21

6 2023-11-22

Bericht 1

📚 fdv - Chp 14

7 2023-11-29

Descriptive Stats

📚 fdv - Chp 29

8 2023-12-06

Reading in data

📃 Six part series on W.E.B. Du Bois’ legacy

9 2023-12-13

Wrangling 2: Tidying data

📚 fdv - Chp 10

10 2023-12-20

Data Viz 2: Visual summaries

Vorlesungsfrei 2023-12-27

☃️

🎿

Vorlesungsfrei 2024-01-03

☃️

🎿

11 2024-01-10

Bericht 2

📃 The case against diverging stacked bars
📃 On Likert Scales In R

12 2024-01-17

Writing functions

📃 sf vgnette 1 + 📃 sf vgnette 2 +
📃 sf vgnette 3 + 📃 sf vgnette 4 +
📃 sf vgnette 5

13 2024-01-24

Inferential statistics

📚 fdv - Chp 19
📚 fdv - Chp 4

14 2024-01-31

Data Viz 3: visualising your model

📃 gganimate vignette

15 2024-02-07

Bericht 3

16 2024-02-14

Open session: Q&A

Course Overview
Kursübersicht
Quellcode
---
lang: de
execute:
  echo: false
bibliography: references.bib
csl: apa.csl
---

```{r, eval = T, cache = F}
rbbt::bbt_update_bib("syllabus.qmd")
```

# Syllabus {.unnumbered}

```{r}
pacman::p_load(dplyr,
               lubridate,
               googlesheets4,
               gt,
               timesaveR)
```

```{r}
# tell googlesheets4 we don't want private
gs4_deauth()
```



```{r}
#| eval: true

# Create syllabus structure ####

# define negative %in%; don't end up using this I think
'%ni%' <- Negate("%in%")

# create tibble containing all weekly dates from first lecture until last
dates <- tibble(
  Datum = as.character(seq(ymd("2023-10-18"), ymd("2024-2-14"), by = "weeks")))

# create vector with dates of holidays
holidays <- c("2024-01-03",
              "2023-12-27" )

# remove holiday dates and add Woche, which lists the week number
syllabus <-
  dates |> 
  mutate(class = ifelse(Datum %in% holidays, "Vorlesungsfrei", "class")) |> 
  mutate(Woche = 1:length(Datum), .by = class, .before = Datum) |> 
  mutate(Woche = ifelse(Datum %in% holidays, "Vorlesungsfrei", Woche)) |> 
  select(-class)
```

```{r}
# inspiration: https://github.com/vizdata-s23/vizdata-s23/blob/main/index.qmd
content <- 
  googlesheets4::read_sheet("https://docs.google.com/spreadsheets/d/1zg0Rb5S8p4oggjWxMU60zC8aFTJIblx3pAuI0SON4AY/edit?usp=sharing") |> 
  mutate(Woche = as.character(Woche),
         Thema = ifelse(is.na(topic_link), topic,
                        paste0(
                          "[",topic,"]",
                          "(","https://daniela-palleschi.github.io/ba-datenverarbeitung-wise23/",topic_link,")")), 
         Vorbereitung = ifelse(is.na(prepare_link), prepare,
                               paste0("[",prepare,"]","(",prepare_link,")"))) |> 
  select(Woche, Thema, Vorbereitung)
```

```{r}
left_join(
  syllabus, content, by = "Woche"
) |> 
  gt() |>
  sub_missing(columns = c(Woche, Thema, Vorbereitung), missing_text = "") |>
  cols_align(
    align = "center", 
    columns = c(Woche)
    ) |>
  cols_align(
    align = "left", 
    columns = c(Thema, Vorbereitung)
    ) |>
  tab_style(
    style = cell_borders(
      sides = "right",
      color = "#D3D3D3",
      style = "solid"
    ),
    locations = cells_body(
      columns = c(Thema, Vorbereitung)
    )
  ) |>
  fmt_markdown(
    columns = c(Thema, Vorbereitung)
  ) |>
  cols_width(
    Woche ~ px(150),
    Thema ~ px(400),
    Vorbereitung ~ px(300)
  ) 
```